Search results for: automatic localisation
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 634

Search results for: automatic localisation

574 Bit Error Rate Monitoring for Automatic Bias Control of Quadrature Amplitude Modulators

Authors: Naji Ali Albakay, Abdulrahman Alothaim, Isa Barshushi

Abstract:

The most common quadrature amplitude modulator (QAM) applies two Mach-Zehnder Modulators (MZM) and one phase shifter to generate high order modulation format. The bias of MZM changes over time due to temperature, vibration, and aging factors. The change in the biasing causes distortion to the generated QAM signal which leads to deterioration of bit error rate (BER) performance. Therefore, it is critical to be able to lock MZM’s Q point to the required operating point for good performance. We propose a technique for automatic bias control (ABC) of QAM transmitter using BER measurements and gradient descent optimization algorithm. The proposed technique is attractive because it uses the pertinent metric, BER, which compensates for bias drifting independently from other system variations such as laser source output power. The proposed scheme performance and its operating principles are simulated using OptiSystem simulation software for 4-QAM and 16-QAM transmitters.

Keywords: Automatic bias control, optical fiber communication, optical modulation, optical devices.

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573 Earphone Style Wearable Device for Automatic Guidance Service with Position Sensing

Authors: Dawei Cai

Abstract:

This paper describes a design of earphone style wearable device that may provide an automatic guidance service for visitors. With both position information and orientation information obtained from NFC and terrestrial magnetism sensor, a high level automatic guide service may be realized. To realize the service, a algorithm for position detection using the packet from NFC tags, and developed an algorithm to calculate the device orientation based on the data from acceleration and terrestrial magnetism sensors called as MEMS. If visitors want to know some explanation about an exhibit in front of him, what he has to do is only move to the object and stands for a moment. The identification program will automatically recognize the status based on the information from NFC and MEMS, and start playing explanation content about the exhibit. This service should be useful for improving the understanding of the exhibition items and bring more satisfactory visiting experience without less burden.

Keywords: Wearable device, MEMS sensor, NFC, ubiquitous computing, guide system.

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572 Automatic Clustering of Gene Ontology by Genetic Algorithm

Authors: Razib M. Othman, Safaai Deris, Rosli M. Illias, Zalmiyah Zakaria, Saberi M. Mohamad

Abstract:

Nowadays, Gene Ontology has been used widely by many researchers for biological data mining and information retrieval, integration of biological databases, finding genes, and incorporating knowledge in the Gene Ontology for gene clustering. However, the increase in size of the Gene Ontology has caused problems in maintaining and processing them. One way to obtain their accessibility is by clustering them into fragmented groups. Clustering the Gene Ontology is a difficult combinatorial problem and can be modeled as a graph partitioning problem. Additionally, deciding the number k of clusters to use is not easily perceived and is a hard algorithmic problem. Therefore, an approach for solving the automatic clustering of the Gene Ontology is proposed by incorporating cohesion-and-coupling metric into a hybrid algorithm consisting of a genetic algorithm and a split-and-merge algorithm. Experimental results and an example of modularized Gene Ontology in RDF/XML format are given to illustrate the effectiveness of the algorithm.

Keywords: Automatic clustering, cohesion-and-coupling metric, gene ontology; genetic algorithm, split-and-merge algorithm.

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571 Automatic Segmentation of Retina Vessels by Using Zhang Method

Authors: Ehsan Saghapour, Somayeh Zandian

Abstract:

Image segmentation is an important step in image processing. Major developments in medical imaging allow physicians to use potent and non-invasive methods in order to evaluate structures, performance and to diagnose human diseases. In this study, an active contour was used to extract vessel networks from color retina images. Automatic analysis of retina vessels facilitates calculation of arterial index which is required to diagnose some certain retinopathies.

Keywords: Active contour, retinal vessel segmentation, image processing.

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570 Defining a Semantic Web-based Framework for Enabling Automatic Reasoning on CIM-based Management Platforms

Authors: Fernando Alonso, Rafael Fernandez, Sonia Frutos, Javier Soriano

Abstract:

CIM is the standard formalism for modeling management information developed by the Distributed Management Task Force (DMTF) in the context of its WBEM proposal, designed to provide a conceptual view of the managed environment. In this paper, we propose the inclusion of formal knowledge representation techniques, based on Description Logics (DLs) and the Web Ontology Language (OWL), in CIM-based conceptual modeling, and then we examine the benefits of such a decision. The proposal is specified as a CIM metamodel level mapping to a highly expressive subset of DLs capable of capturing all the semantics of the models. The paper shows how the proposed mapping provides CIM diagrams with precise semantics and can be used for automatic reasoning about the management information models, as a design aid, by means of newgeneration CASE tools, thanks to the use of state-of-the-art automatic reasoning systems that support the proposed logic and use algorithms that are sound and complete with respect to the semantics. Such a CASE tool framework has been developed by the authors and its architecture is also introduced. The proposed formalization is not only useful at design time, but also at run time through the use of rational autonomous agents, in response to a need recently recognized by the DMTF.

Keywords: CIM, Knowledge-based Information Models, OntologyLanguages, OWL, Description Logics, Integrated Network Management, Intelligent Agents, Automatic Reasoning Techniques.

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569 PID Control Design Based on Genetic Algorithm with Integrator Anti-Windup for Automatic Voltage Regulator and Speed Governor of Brushless Synchronous Generator

Authors: O. S. Ebrahim, M. A. Badr, Kh. H. Gharib, H. K. Temraz

Abstract:

This paper presents a methodology based on genetic algorithm (GA) to tune the parameters of proportional-integral-differential (PID) controllers utilized in the automatic voltage regulator (AVR) and speed governor of a brushless synchronous generator driven by three-stage steam turbine. The parameter tuning is represented as a nonlinear optimization problem solved by GA to minimize the integral of absolute error (IAE). The problem of integral windup due to physical system limitations is solved using simple anti-windup scheme. The obtained controllers are compared to those designed using classical Ziegler-Nichols technique and constrained optimization. Results show distinct superiority of the proposed method.

Keywords: Brushless synchronous generator, Genetic Algorithm, GA, Proportional-Integral-Differential control, PID control, automatic voltage regulator, AVR.

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568 Automatic Number Plate Recognition System Based on Deep Learning

Authors: T. Damak, O. Kriaa, A. Baccar, M. A. Ben Ayed, N. Masmoudi

Abstract:

In the last few years, Automatic Number Plate Recognition (ANPR) systems have become widely used in the safety, the security, and the commercial aspects. Forethought, several methods and techniques are computing to achieve the better levels in terms of accuracy and real time execution. This paper proposed a computer vision algorithm of Number Plate Localization (NPL) and Characters Segmentation (CS). In addition, it proposed an improved method in Optical Character Recognition (OCR) based on Deep Learning (DL) techniques. In order to identify the number of detected plate after NPL and CS steps, the Convolutional Neural Network (CNN) algorithm is proposed. A DL model is developed using four convolution layers, two layers of Maxpooling, and six layers of fully connected. The model was trained by number image database on the Jetson TX2 NVIDIA target. The accuracy result has achieved 95.84%.

Keywords: Automatic number plate recognition, character segmentation, convolutional neural network, CNN, deep learning, number plate localization.

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567 Automatic Design Algorithm for the Tower Crane Foundations

Authors: Sungho Lee, Goonjae Lee, Chaeyeon Lim, Sunkuk Kim

Abstract:

Foundation of tower crane serves to ensure stability against vertical and horizontal forces. If foundation stress is not sufficient, tower crane may be subject to overturning, shearing or foundation settlement. Therefore, engineering review of stable support is a highly critical part of foundation design. However, there are not many professionals who can conduct engineering review of tower crane foundation and, if any, they have information only on a small number of cranes in which they have hands-on experience. It is also customary to rely on empirical knowledge and tower crane renter-s recommendations rather than designing foundation on the basis of engineering knowledge. Therefore, a foundation design automation system considering not only lifting conditions but also overturning risk, shearing and vertical force may facilitate production of foolproof foundation design for experts and enable even non-experts to utilize professional knowledge that only experts can access now. This study proposes Automatic Design Algorithm for the Tower Crane Foundations considering load and horizontal force.

Keywords: Tower Crane, Automatic Design, Foundations, Optimization Algorithm, Stability

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566 Determination of Neighbor Node in Consideration of the Imaging Range of Cameras in Automatic Human Tracking System

Authors: Kozo Tanigawa, Tappei Yotsumoto, Kenichi Takahashi, Takao Kawamura, Kazunori Sugahara

Abstract:

A automatic human tracking system using mobile agent technology is realized because a mobile agent moves in accordance with a migration of a target person. In this paper, we propose a method for determining the neighbor node in consideration of the imaging range of cameras.

Keywords: Human tracking, Mobile agent, Pan/Tilt/Zoom, Neighbor relation.

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565 Automatic Flood Prediction Using Rainfall Runoff Model in Moravian-Silesian Region

Authors: B. Sir, M. Podhoranyi, S. Kuchar, T. Kocyan

Abstract:

Rainfall runoff models play important role in hydrological predictions. However, the model is only one part of the process for creation of flood prediction. The aim of this paper is to show the process of successful prediction for flood event (May 15 – May 18 2014). Prediction was performed by rainfall runoff model HEC–HMS, one of the models computed within Floreon+ system. The paper briefly evaluates the results of automatic hydrologic prediction on the river Olše catchment and its gages Český Těšín and Věřňovice.

Keywords: Flood, HEC-HMS, Prediction, Rainfall – Runoff.

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564 The Hyperbolic Smoothing Approach for Automatic Calibration of Rainfall-Runoff Models

Authors: Adilson Elias Xavier, Otto Corrêa Rotunno Filho, Paulo Canedo de Magalhães

Abstract:

This paper addresses the issue of automatic parameter estimation in conceptual rainfall-runoff (CRR) models. Due to threshold structures commonly occurring in CRR models, the associated mathematical optimization problems have the significant characteristic of being strongly non-differentiable. In order to face this enormous task, the resolution method proposed adopts a smoothing strategy using a special C∞ differentiable class function. The final estimation solution is obtained by solving a sequence of differentiable subproblems which gradually approach the original conceptual problem. The use of this technique, called Hyperbolic Smoothing Method (HSM), makes possible the application of the most powerful minimization algorithms, and also allows for the main difficulties presented by the original CRR problem to be overcome. A set of computational experiments is presented for the purpose of illustrating both the reliability and the efficiency of the proposed approach.

Keywords: Rainfall-runoff models, optimization procedure, automatic parameter calibration, hyperbolic smoothing method.

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563 Hardware-in-the-Loop Test for Automatic Voltage Regulator of Synchronous Condenser

Authors: Ha Thi Nguyen, Guangya Yang, Arne Hejde Nielsen, Peter Højgaard Jensen

Abstract:

Automatic voltage regulator (AVR) plays an important role in volt/var control of synchronous condenser (SC) in power systems. Test AVR performance in steady-state and dynamic conditions in real grid is expensive, low efficiency, and hard to achieve. To address this issue, we implement hardware-in-the-loop (HiL) test for the AVR of SC to test the steady-state and dynamic performances of AVR in different operating conditions. Startup procedure of the system and voltage set point changes are studied to evaluate the AVR hardware response. Overexcitation, underexcitation, and AVR set point loss are tested to compare the performance of SC with the AVR hardware and that of simulation. The comparative results demonstrate how AVR will work in a real system. The results show HiL test is an effective approach for testing devices before deployment and is able to parameterize the controller with lower cost, higher efficiency, and more flexibility.

Keywords: Automatic voltage regulator, hardware-in-the-loop, synchronous condenser, real time digital simulator.

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562 Defining Programming Problems as Learning Objects

Authors: José Paulo Leal, Ricardo Queirós

Abstract:

Standards for learning objects focus primarily on content presentation. They were already extended to support automatic evaluation but it is limited to exercises with a predefined set of answers. The existing standards lack the metadata required by specialized evaluators to handle types of exercises with an indefinite set of solutions. To address this issue existing learning object standards were extended to the particular requirements of a specialized domain. A definition of programming problems as learning objects, compatible both with Learning Management Systems and with systems performing automatic evaluation of programs, is presented in this paper. The proposed definition includes metadata that cannot be conveniently represented using existing standards, such as: the type of automatic evaluation; the requirements of the evaluation engine; and the roles of different assets - tests cases, program solutions, etc. The EduJudge project and its main services are also presented as a case study on the use of the proposed definition of programming problems as learning objects.

Keywords: Content Packaging, eLearning Services, Interoperability, Learning Objects.

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561 From Modeling of Data Structures towards Automatic Programs Generating

Authors: Valentin P. Velikov

Abstract:

Automatic program generation saves time, human resources, and allows receiving syntactically clear and logically correct modules. The 4-th generation programming languages are related to drawing the data and the processes of the subject area, as well as, to obtain a frame of the respective information system. The application can be separated in interface and business logic. That means, for an interactive generation of the needed system to be used an already existing toolkit or to be created a new one.

Keywords: Computer science, graphical user interface, user dialog interface, dialog frames, data modeling, subject area modeling.

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560 Comparing SVM and Naïve Bayes Classifier for Automatic Microaneurysm Detections

Authors: A. Sopharak, B. Uyyanonvara, S. Barman

Abstract:

Diabetic retinopathy is characterized by the development of retinal microaneurysms. The damage can be prevented if disease is treated in its early stages. In this paper, we are comparing Support Vector Machine (SVM) and Naïve Bayes (NB) classifiers for automatic microaneurysm detection in images acquired through non-dilated pupils. The Nearest Neighbor classifier is used as a baseline for comparison. Detected microaneurysms are validated with expert ophthalmologists’ hand-drawn ground-truths. The sensitivity, specificity, precision and accuracy of each method are also compared.

Keywords: Diabetic retinopathy, microaneurysm, Naïve Bayes classifier, SVM classifier.

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559 CACSC tool for Automatic Design of Robust Controllers for Hydropower Plants

Authors: Jose J.CarreñoZagarra, Rodolfo Villamizar Mejía

Abstract:

This work describes a CACSD tool for automatic design of robust controllers for hydraulic turbines. The tool calculates the optimal  controller using the MATLAB hinfopt function and it serves as a practical and effective solution for the laborious task of designing a different controller for each type of turbine and generator, and different parameters and conditions of the plant. Results of the simulation of a generating unit subject to parameters variation show the accuracy and efficiency of the obtained robust controllers.

Keywords: Robust Control, Hydroelectric System Turbine, Control H∞, CACSD

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558 A Proposal of an Automatic Formatting Method for Transforming XML Data

Authors: Zhe JIN, Motomichi TOYAMA

Abstract:

PPX(Pretty Printer for XML) is a query language that offers a concise description method of formatting the XML data into HTML. In this paper, we propose a simple specification of formatting method that is a combination description of automatic layout operators and variables in the layout expression of the GENERATE clause of PPX. This method can automatically format irregular XML data included in a part of XML with layout decision rule that is referred to DTD. In the experiment, a quick comparison shows that PPX requires far less description compared to XSLT or XQuery programs doing same tasks.

Keywords: PPX, Irregular XML data, Layout decision rule, HTML.

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557 A Study of Dose Distribution and Image Quality under an Automatic Tube Current Modulation (ATCM) System for a Toshiba Aquilion 64 CT Scanner Using a New Design of Phantom

Authors: S. Sookpeng, C. J. Martin, D. J. Gentle

Abstract:

Automatic tube current modulation (ATCM) systems are available for all CT manufacturers and are used for the majority of patients. Understanding how the systems work and their influence on patient dose and image quality is important for CT users, in order to gain the most effective use of the systems. In the present study, a new phantom was used for evaluating dose distribution and image quality under the ATCM operation for the Toshiba Aquilion 64 CT scanner using different ATCM options and a fixed mAs technique. A routine chest, abdomen and pelvis (CAP) protocol was selected for study and Gafchromic film was used to measure entrance surface dose (ESD), peripheral dose and central axis dose in the phantom. The results show the dose reductions achievable with various ATCM options, in relation with the target noise. The doses and image noise distribution were more uniform when the ATCM system was implemented compared with the fixed mAs technique. The lower limit set for the tube current will affect the modulations especially for the lower dose option. This limit prevented the tube current being reduced further and therefore the lower dose ATCM setting resembled a fixed mAs technique. Selection of a lower tube current limit is likely to reduce doses for smaller patients in scans of chest and neck regions.

Keywords: Computed Tomography (CT), Automatic Tube Current Modulation (ATCM), Automatic Exposure Control (AEC).

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556 Robust Heart Sounds Segmentation Based on the Variation of the Phonocardiogram Curve Length

Authors: Mecheri Zeid Belmecheri, Maamar Ahfir, Izzet Kale

Abstract:

Automatic cardiac auscultation is still a subject of research in order to establish an objective diagnosis. Recorded heart sounds as Phonocardiogram (PCG) signals can be used for automatic segmentation into components that have clinical meanings. These are the first sound, S1, the second sound, S2, and the systolic and diastolic components, respectively. In this paper, an automatic method is proposed for the robust segmentation of heart sounds. This method is based on calculating an intermediate sawtooth-shaped signal from the length variation of the recorded PCG signal in the time domain and, using its positive derivative function that is a binary signal in training a Recurrent Neural Network (RNN). Results obtained in the context of a large database of recorded PCGs with their simultaneously recorded Electrocardiograms (ECGs) from different patients in clinical settings, including normal and abnormal subjects, show on average a segmentation testing performance average of 76% sensitivity and 94% specificity.

Keywords: Heart sounds, PCG segmentation, event detection, Recurrent Neural Networks, PCG curve length.

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555 Automatic Detection of Syllable Repetition in Read Speech for Objective Assessment of Stuttered Disfluencies

Authors: K. M. Ravikumar, Balakrishna Reddy, R. Rajagopal, H. C. Nagaraj

Abstract:

Automatic detection of syllable repetition is one of the important parameter in assessing the stuttered speech objectively. The existing method which uses artificial neural network (ANN) requires high levels of agreement as prerequisite before attempting to train and test ANNs to separate fluent and nonfluent. We propose automatic detection method for syllable repetition in read speech for objective assessment of stuttered disfluencies which uses a novel approach and has four stages comprising of segmentation, feature extraction, score matching and decision logic. Feature extraction is implemented using well know Mel frequency Cepstra coefficient (MFCC). Score matching is done using Dynamic Time Warping (DTW) between the syllables. The Decision logic is implemented by Perceptron based on the score given by score matching. Although many methods are available for segmentation, in this paper it is done manually. Here the assessment by human judges on the read speech of 10 adults who stutter are described using corresponding method and the result was 83%.

Keywords: Assessment, DTW, MFCC, Objective, Perceptron, Stuttering.

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554 A Forward Automatic Censored Cell-Averaging Detector for Multiple Target Situations in Log-Normal Clutter

Authors: Musa'ed N. Almarshad, Saleh A. Alshebeili, Mourad Barkat

Abstract:

A challenging problem in radar signal processing is to achieve reliable target detection in the presence of interferences. In this paper, we propose a novel algorithm for automatic censoring of radar interfering targets in log-normal clutter. The proposed algorithm, termed the forward automatic censored cell averaging detector (F-ACCAD), consists of two steps: removing the corrupted reference cells (censoring) and the actual detection. Both steps are performed dynamically by using a suitable set of ranked cells to estimate the unknown background level and set the adaptive thresholds accordingly. The F-ACCAD algorithm does not require any prior information about the clutter parameters nor does it require the number of interfering targets. The effectiveness of the F-ACCAD algorithm is assessed by computing, using Monte Carlo simulations, the probability of censoring and the probability of detection in different background environments.

Keywords: CFAR, Log-normal clutter, Censoring, Probabilityof detection, Probability of false alarm, Probability of falsecensoring.

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553 Semi-Automatic Approach for Semantic Annotation

Authors: Mohammad Yasrebi, Mehran Mohsenzadeh

Abstract:

The third phase of web means semantic web requires many web pages which are annotated with metadata. Thus, a crucial question is where to acquire these metadata. In this paper we propose our approach, a semi-automatic method to annotate the texts of documents and web pages and employs with a quite comprehensive knowledge base to categorize instances with regard to ontology. The approach is evaluated against the manual annotations and one of the most popular annotation tools which works the same as our tool. The approach is implemented in .net framework and uses the WordNet for knowledge base, an annotation tool for the Semantic Web.

Keywords: Semantic Annotation, Metadata, Information Extraction, Semantic Web, knowledge base.

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552 Automatic Generation Control of Interconnected Power System with Generation Rate Constraintsby Hybrid Neuro Fuzzy Approach

Authors: Gayadhar Panda, Sidhartha Panda, C. Ardil

Abstract:

The design of Automatic Generation Control (AGC) system plays a vital role in automation of power system. This paper proposes Hybrid Neuro Fuzzy (HNF) approach for AGC of two-area interconnected reheat thermal power system with the consideration of Generation Rate Constraint (GRC). The advantage of proposed controller is that it can handle the system non-linearities and at the same time the proposed approach is faster than conventional controllers. The performance of HNF controller has been compared with that of both conventional Proportional Integral (PI) controller as well as Fuzzy Logic Controller (FLC) both in the absence and presence of Generation Rate Constraint (GRC). System performance is examined considering disturbance in each area of interconnected power system.

Keywords: Automatic Generation Control (AGC), Dynamic Response, Generation Rate Constraint (GRC), Proportional Integral(PI) Controller, Fuzzy Logic Controller (FLC), Hybrid Neuro-Fuzzy(HNF) Control, MATLAB/SIMULINK.

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551 Automatic Checkpoint System Using Face and Card Information

Authors: Kriddikorn Kaewwongsri, Nikom Suvonvorn

Abstract:

In the deep south of Thailand, checkpoints for people verification are necessary for the security management of risk zones, such as official buildings in the conflict area. In this paper, we propose an automatic checkpoint system that verifies persons using information from ID cards and facial features. The methods for a person’s information abstraction and verification are introduced based on useful information such as ID number and name, extracted from official cards, and facial images from videos. The proposed system shows promising results and has a real impact on the local society.

Keywords: Face comparison, card recognition, OCR, checkpoint system, authentication.

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550 Providing Medical Information in Braille: Research and Development of Automatic Braille Translation Program for Japanese “eBraille“

Authors: Aki Sugano, Mika Ohta, Mineko Ikegami, Kenji Miura, Sayo Tsukamoto, Akihiro Ichinose, Toshiko Ohshima, Eiichi Maeda, Masako Matsuura, Yutaka Takao

Abstract:

Along with the advances in medicine, providing medical information to individual patient is becoming more important. In Japan such information via Braille is hardly provided to blind and partially sighted people. Thus we are researching and developing a Web-based automatic translation program “eBraille" to translate Japanese text into Japanese Braille. First we analyzed the Japanese transcription rules to implement them on our program. We then added medical words to the dictionary of the program to improve its translation accuracy for medical text. Finally we examined the efficacy of statistical learning models (SLMs) for further increase of word segmentation accuracy in braille translation. As a result, eBraille had the highest translation accuracy in the comparison with other translation programs, improved the accuracy for medical text and is utilized to make hospital brochures in braille for outpatients and inpatients.

Keywords: Automatic Braille translation, Medical text, Partially sighted people.

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549 Improved Feature Extraction Technique for Handling Occlusion in Automatic Facial Expression Recognition

Authors: Khadijat T. Bamigbade, Olufade F. W. Onifade

Abstract:

The field of automatic facial expression analysis has been an active research area in the last two decades. Its vast applicability in various domains has drawn so much attention into developing techniques and dataset that mirror real life scenarios. Many techniques such as Local Binary Patterns and its variants (CLBP, LBP-TOP) and lately, deep learning techniques, have been used for facial expression recognition. However, the problem of occlusion has not been sufficiently handled, making their results not applicable in real life situations. This paper develops a simple, yet highly efficient method tagged Local Binary Pattern-Histogram of Gradient (LBP-HOG) with occlusion detection in face image, using a multi-class SVM for Action Unit and in turn expression recognition. Our method was evaluated on three publicly available datasets which are JAFFE, CK, SFEW. Experimental results showed that our approach performed considerably well when compared with state-of-the-art algorithms and gave insight to occlusion detection as a key step to handling expression in wild.

Keywords: Automatic facial expression analysis, local binary pattern, LBP-HOG, occlusion detection.

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548 Improving the Design of Blood Pressure and Blood Saturation Monitors

Authors: L. Parisi

Abstract:

A blood pressure monitor or sphygmomanometer can be either manual or automatic, employing respectively either the auscultatory method or the oscillometric method. The manual version of the sphygmomanometer involves an inflatable cuff with a stethoscope adopted to detect the sounds generated by the arterial walls to measure blood pressure in an artery. An automatic sphygmomanometer can be effectively used to monitor blood pressure through a pressure sensor, which detects vibrations provoked by oscillations of the arterial walls. The pressure sensor implemented in this device improves the accuracy of the measurements taken.

Keywords: Blood pressure, blood saturation, sensors, actuators, design improvement.

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547 Design of an Artificial Intelligence Based Automatic Task Planner or a Robotic System

Authors: T. C. Manjunath, C. Ardil

Abstract:

This paper deals with the design and the implementation of an automatic task planner for a robot, irrespective of whether it is a stationary robot or a mobile robot. The aim of the task planner nothing but, they are planning systems which are used to plan a particular task and do the robotic manipulation. This planning system is embedded into the system software in the computer, which is interfaced to the computer. When the instructions are given using the computer, this is transformed into real time application using the robot. All the AI based algorithms are written and saved in the control software, which acts as the intelligent task planning system.

Keywords: AI, Robot, Task Planner, RT, Algorithm, Specs, Controller.

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546 Automatic Change Detection for High-Resolution Satellite Images of Urban and Suburban Areas

Authors: Antigoni Panagiotopoulou, Lemonia Ragia

Abstract:

High-resolution satellite images can provide detailed information about change detection on the earth. In the present work, QuickBird images of spatial resolution 60 cm/pixel and WorldView images of resolution 30 cm/pixel are utilized to perform automatic change detection in urban and suburban areas of Crete, Greece. There is a relative time difference of 13 years among the satellite images. Multiindex scene representation is applied on the images to classify the scene into buildings, vegetation, water and ground. Then, automatic change detection is made possible by pixel-per-pixel comparison of the classified multi-temporal images. The vegetation index and the water index which have been developed in this study prove effective. Furthermore, the proposed change detection approach not only indicates whether changes have taken place or not but also provides specific information relative to the types of changes. Experimentations with other different scenes in the future could help optimize the proposed spectral indices as well as the entire change detection methodology.

Keywords: Change detection, multiindex scene representation, spectral index, QuickBird, WorldView.

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545 An Automatic Model Transformation Methodology Based on Semantic and Syntactic Comparisons and the Granularity Issue Involved

Authors: Tiexin Wang, Sebastien Truptil, Frederick Benaben

Abstract:

Model transformation, as a pivotal aspect of Modeldriven engineering, attracts more and more attentions both from researchers and practitioners. Many domains (enterprise engineering, software engineering, knowledge engineering, etc.) use model transformation principles and practices to serve to their domain specific problems; furthermore, model transformation could also be used to fulfill the gap between different domains: by sharing and exchanging knowledge. Since model transformation has been widely used, there comes new requirement on it: effectively and efficiently define the transformation process and reduce manual effort that involved in. This paper presents an automatic model transformation methodology based on semantic and syntactic comparisons, and focuses particularly on granularity issue that existed in transformation process. Comparing to the traditional model transformation methodologies, this methodology serves to a general purpose: crossdomain methodology. Semantic and syntactic checking measurements are combined into a refined transformation process, which solves the granularity issue. Moreover, semantic and syntactic comparisons are supported by software tool; manual effort is replaced in this way.

Keywords: Automatic model transformation, granularity issue, model-driven engineering, semantic and syntactic comparisons.

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